International Journal of Engineering and Computer Science <p style="font-weight: 400;"><strong>International Journal Of Engineering And Computer Science </strong></p> <p style="font-weight: 400;">IJECS is a leading international journals for publication of new ideas, the state of the art research results and fundamental advances in all aspects of computer science and engineering. IJECS is a scholarly open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications related to Computer Science and Engineering</p> <p style="font-weight: 400;">It is an international journal intended for professionals and researchers in all fields of computer science and electronics. The IJECS publishes research articles and reviews within the whole field computer science &amp; engineering, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject.</p> <p style="font-weight: 400;">IJECS welcomes the submission of documents relating to any branch of the Theory of Computing and Engineering and its applications in business, industry and other topics. The topics covered by the journal include artificial intelligence, bioinformatics, computational statistics, database, data mining, financial engineering, hardware systems, imaging engineering, industrial engineering, internet computing, networking, operations research scientific computing, software engineering and its applications</p> <p style="font-weight: 400;"><strong>Editorial Policy&nbsp;</strong></p> <p style="font-weight: 400;">Authors should prepare their manuscripts according to the instructions given in the authors' guidelines. Manuscripts which do not conform to the format and style of the Journal may be returned to the authors for revision or rejected. The Journal reserves the right to make any further formal changes and language corrections necessary in a manuscript accepted for publication so that it conforms to the formatting requirements of the Journal</p> <p style="font-weight: 400;"><strong>Why IJECS&nbsp;</strong></p> <ul> <li class="show" style="font-weight: 400;">&nbsp; &nbsp;IJECS is an International, Peer reviewed, Open Access Journal</li> <li class="show" style="font-weight: 400;">&nbsp; &nbsp;Paper will publish immediately in current issue after registration</li> <li class="show" style="font-weight: 400;">&nbsp; &nbsp;IJECS accepts original and high quality research and technical papers</li> <li class="show" style="font-weight: 400;">&nbsp; &nbsp;Authors can download their full length paper at any time</li> <li class="show" style="font-weight: 400;">&nbsp; &nbsp;frequency of publication Monthly</li> </ul> <p>Articles of IJECS are subjected to peer reviewing and these are included in the standard indexing databases like Cross Ref DOI, Index Copernicus (IC Value), Scientific Indexing Services SIS, Directory&nbsp;of&nbsp;Open Access Journals DOAJ, Directory&nbsp;of&nbsp;Research Journals Indexing DRJI, Google Scholar, Research Bible, New Jour, Jour Informatics, Science&nbsp;Center.</p> <p style="font-weight: 400;"><strong>Important notice</strong></p> <p>Authors can now directly send their manuscript as an email attachment to;</p> <p>All manuscripts are subject to rapid peer review. Those of high quality (not previously published and not under consideration for publication in another journal) will be published without delay. First-time users are required to register themselves as an author before making submissions by signing up the author registration form at journals website</p> <p>www.</p> <p>With the online journal management system that we are using, authors will be able to track manuscripts progress through the editorial process by logging in as author in authors Dashboard.</p> <p><strong>Top Reasons for publication with us</strong></p> <p><strong>Quick Quality Review:</strong>&nbsp;The journal has strong international team of editors and reviewers, Rapid Decision and Publication</p> <p><strong>Very Low Publication Fees:</strong>&nbsp;Comparable journals charge a huge sum for each accepted manuscript. IJEECS only charge the fees necessary to recoup cost associated with running the journal</p> <p>IJECS would take much care in making your article published without much delay with your kind cooperation.</p> <p>IJECS hopes that Researchers, Research scholars, Academician, Industrialists, Consultancy etc. would make use of this journal publication for the development of science and technology</p> International Journal of Engineering and Computer Science en-US International Journal of Engineering and Computer Science 2319-7242 An efficient clustering algorithm for max link selection on CRN <p>Lifetime enhancement has always been a crucial issue as most of the cognitive radio network (CRNs) operates in unattended environment where human access and monitoring are practically infeasible. Clustering is one of the most powerful techniques that can arrange the system operation in associated manner to attend the network scalability, minimize energy consumption and achieve prolonged network lifetime. To conquer this issue, current researchers have triggered the proposition of many numerous clustering algorithms. However, most of the proposed algorithms overburden the cluster head (CH) during cluster formation. To overcome this problem, many researchers have come up with the idea of fuzzy logic (FL), which is applied in CRN for decision making. These algorithms focus on the efficiency of CH, which could be adoptive, flexible, and intelligent enough to distribute the load among the sensor nodes that can enhance the network lifetime. But unfortunately, most of the algorithms use type-1 FL (T1FL) model. In this work, we propose a clustering algorithm on the basis of interval type-2 FL model, expecting to handle uncertain level decision better than T1FL model.</p> Mahiboob Pasha RM Surendranath H ##submission.copyrightStatement## 2019-09-13 2019-09-13 8 09 24834 24837 Mamdani-Fuzzy Framework for Academic Staff Selection and Placement in Nigerian Universities <p>Selection and placement of appropriate personnel for the right job leads to great success in any organization. However, this is one of the most important activities carried out by Human Resource (HR). Minimizing imprecision and subjective value judgment in personnel selection processes were taken into consideration in this research by developing personnel selection and placement framework using the Mamdani- fuzzy model. This research work is aimed at developing Mamdani- fuzzy framework for academic staff selection and placement. A model with three levels has been developed to manage the database, and the necessary conditions required from applicants for selection and placement, and the consideration of individual temperament was paramount. Tools: Java script and HTML (for the front end) PHP and MySQL (for the database storage as back end).&nbsp; Experimental results using fuzzy classification membership function defined by the truth value of a fuzzy propositional function would also be used as part of the analysis and design. When the need arise, MathLab would be employed for some analysis and simulations. A graphical user interface (GUI) would be developed for all the relevant forms in order to effectively interact with the users of the system</p> Ibrahim Manga S.D. Samaila H. Bello ##submission.copyrightStatement## 2019-09-19 2019-09-19 8 09 24838 24846 10.18535/ijecs/v8i09.4362 Stock Market Prediction using Machine Learning and Cloud Computing <p>In the world with increasing globalization , where money places a crucial role in determining the expansion and earnings of a company trading places a very crucial role. Multiple companies invest millions and billions of dollars in other countries with an expectation to make profits. In such a risky business Predicting the movement of the market can help companies or individual in making good decisions and can prevent severe loses. In this research paper we will discuss how we can use the computational power of the computer on cloud along with the machine learning algorithms to predict the closing values of the stocks which is a big challenge otherwise. For this purpose we will use Python as our programming language which supports a lot of ML based Libraries. The models we will be using are SVM(Support Vector Machine) , Linear Regression , Random Forest, XGBoost ,LSTM for deep learning</p> Nirbhay Narkhede ##submission.copyrightStatement## 2019-09-26 2019-09-26 8 09 24847 24850 10.18535/ijecs/v8i09.4361